Big Data analytics have increasingly gained prominence in business because it has provided beneficial insights regarding emerging trends, behaviors and preferences drawn from millions of touchpoints companies have of customers. It is a powerful and helpful tool companies should continue to invest in. Relying exclusively on big data analytics to address the vast majority of business uncertainties, however, has proven detrimental to our ability to solve problems because more numbers do not necessarily produce more insights (Wang, 2013). Unfortunately, as Maxwell points out, “people are getting caught up on the quantity side of the equation rather than the quality of business insights that analytics can unearth.” Madsbjerg and Rasmussen, in a WSJ article, insightfully captures the essence: “By outsourcing our thinking to Big Data, our ability to make sense of the world by careful observation begins to wither, just as you miss the feel and texture of a new city by navigating it only with the help of a GPS.”

If we are to gain a better understanding of our customers and the business itself, we must not miss nor marginalize “the feel and texture.” We need to see problems and opportunities in terms of human experience and capture and interpret data with a human context. We need to examine and understand “what makes people tick and how they live their lives in their own natural habitats from their own perspective, rather than from traditional business’ perspective (Madsbjerg and Rasmussen, 2014). This applies to markets and products, as much as it applies to corporate culture because humans are complex and difficult to qualify and quantify. By using ethnographic research methods to observe human behavior and its underlying motivations, we can uncover and understand the needs and desires – the whys - the feel and texture - that drive the emotional lives of customers. This type of data is referred to as thick data.

This paper argues for the combined use of big data analytics and thick data ethnography – thick data informing big data and vice versa – a back and forth between what is happening (big data) and why (thick data). For businesses to form a more complete picture, both thick data and big data are needed because each of them generate different types of insights at varying scales and depths (Wang, 2013). As a more complete picture emerges, real and effective solutions and sound decisions to complex business problems may be found. The paper ends with an actual case from extant literature, how, together, big data analytics and thick data ethnography provided insightful advantage.